Pharmacometrics-Based Considerations for the Design of a Pharmacogenomic Clinical Trial Assessing Irinotecan Safety
Purpose Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regar...
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Veröffentlicht in: | Pharmaceutical research 2021-04, Vol.38 (4), p.593-605 |
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Hauptverfasser: | , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
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Zusammenfassung: | Purpose
Pharmacometric models provide useful tools to aid the rational design of clinical trials. This study evaluates study design-, drug-, and patient-related features as well as analysis methods for their influence on the power to demonstrate a benefit of pharmacogenomics (PGx)-based dosing regarding myelotoxicity.
Methods
Two pharmacokinetic and one myelosuppression model were assembled to predict concentrations of irinotecan and its metabolite SN-38 given different UGT1A1 genotypes (poor metabolizers: CL
SN-38
: -36%) and neutropenia following conventional versus PGx-based dosing (350 versus 245 mg/m
2
(-30%)). Study power was assessed given diverse scenarios (
n
= 50–400 patients/arm, parallel/crossover, varying magnitude of CL
SN-38
, exposure-response relationship, inter-individual variability) and using model-based data analysis versus conventional statistical testing.
Results
The magnitude of CL
SN-38
reduction in poor metabolizers and the myelosuppressive potency of SN-38 markedly influenced the power to show a difference in grade 4 neutropenia (80% power with traditional statistical analysis (χ
2
/McNemar’s test, α = 0.05), 220/100 patients per treatment arm/sequence (parallel/crossover study) were required. The model-based analysis resulted in considerably smaller total sample sizes (
n
= 100/15 given parallel/crossover design) to obtain the same statistical power.
Conclusions
The presented findings may help to avoid unfeasible trials and to rationalize the design of pharmacogenetic studies. |
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ISSN: | 0724-8741 1573-904X 1573-904X |
DOI: | 10.1007/s11095-021-03024-w |